class_docstr: Polynomial learning rate schedule.
class_docstr_tok: ["Polynomial","learning","rate","schedule","."]
code: def __call__(self, step):
      linear_warmup = self.lr_warmup_init + (
          tf.cast(step, dtype=tf.float32)
          / self.lr_warmup_step
          * (self.adjusted_lr - self.lr_warmup_init)
      )
      polynomial_lr = self.adjusted_lr * tf.pow(
          1 - (tf.cast(step, dtype=tf.float32) / self.total_steps),
          self.power,
      )
      return tf.where(
          step < self.lr_warmup_step, linear_warmup, polynomial_lr
      )
  
file_path: DALI/docs/examples/use_cases/tensorflow/efficientdet/model/utils/optimizers.py
imports: from absl import logging
  import numpy
  import tensorflow
label_desc: Use image node_id 2 for calling the PolynomialLrSchedule obj's underlying member method code with example usage: obj.__call__(step) and returns: tf